Myelomeningocele (MM), the most common type of spina bifida (SB) (>90% of cases), affects 1 in 2,500 live births in the United States and is the most severe subtype of neural tube defect (NTD) compatible with survival. Mexican Americans (MexA) have the highest prevalence rate in the US with Caucasians Americans (CauA) second. An estimated lifetime of medical care costs (up to 65 years of age) for an individual affected with MM is ~$806,000 (2007 dollars). Occurrence of MM represents a significant economic and public health burden. Genetic contribution to formation of NTDs is complex as is illustrated by the e 240 known mouse models. However, the majority of these mouse models have rostral NTDs while only a handful present with the SB phenotype indicating that SB is more genetically homogeneous. Genetic variation underlying susceptibility and the molecular mechanism(s) involved in the development of human MM is largely unknown. Whole exome sequencing (WES) is the most cost-effective tool to discover all frequency of variations in the exome. We hypothesize that the genetic architecture of MM is comprised of novel/de novo genetic variants identifiable in the exomes of MM subjects by WES, unique variants present in genes known to associate with MM, and genetic variation in novel genes. This proposal utilizes WES to investigate the extent to which rare, novel or de novo variants play a role in human MM. Our immediate objective is to characterize the full spectrum of allelic variations in genes and pathways unique to the exomes of MM subjects to reveal the genetic variability. We will use an enhanced WES protocol to interrogate genetic variations in the exomes of 250 MexA and 250 CauA MM subjects. Ethnic specific variations will be filtered using an exome variation database built from 1,547 MexA exomes of the T2D-GENES project and from 2,649 CauA exomes of the NHLBI Exome Sequencing Project to obtain novel variations. De novo variations will be determined by examining unaffected parents. Characterization of deleterious variants will be determined by functional prediction algorithms. To identify variants influencing MM susceptibility, we will perform logistic regression analysis and gene-based burden tests on genes and pathways according to the rare allele frequency. We will identify variants influencing MM susceptibility prioritized by effect sizes and predicted functional impacts. We will verify association of genes influencing MM susceptibility. Significance of variations in genes and pathways will also be evaluated by meta-analyses. We will replicate ten genes prioritized by occurrence of novel variants, effect sizes and functional impacts in an additional cohort of 250 MexA and 250 CauA MM subjects to verify their influence on MM susceptibility. Completion of the proposed project will define the role of novel/de novo variants to MM susceptibility and create an MM specific exome variants resource that can facilitate future research directions including translation to clinical diagnosis, prediction of outcome and designing treatments.